Empirical comparison of the effects of other party's vehicle type on motorcyclists' injury severity

Abstract

This research explores the various factors influencing the severity of injuries motorcyclists sustain across different collision scenarios. The study considers the types of vehicles involved, including motorcycle (MC), cars, pickup trucks, vans, and trucks. The study is grounded in an analysis of road crashes in Thailand from 2016 to 2019. Recognizing the unique characteristics inherent in each collision type, the study categorizes crashes into six distinct models for a comprehensive analysis. Each model is constructed using the random parameter logit with unobserved heterogeneity in means. Notably, all models incorporate random parameters, with the exception of the MC vs. truck model. Despite some consistent factors across most models, there are noteworthy variations in parameters when comparing different vehicle types. In the context of single-motorcycle crashes, speed limit violation emerges as a critical factor. For the MC vs. MC model, crashes happening from midnight to early morning are significant. The presence of a passenger (pillion) is a key determinant in the MC vs. car model. Meanwhile, in the MC vs. pickup truck model, crashes occurring under poor light conditions from midnight to early morning are of particular importance. The MC vs. van model notably highlights the involvement of male riders. Lastly, the MC vs. truck model draws attention to crashes happening on weekends. By creating specific crash models for diverse vehicle types, this study enhances our understanding of motorcycle crashes. The findings provide valuable insights to inform the development of policies, the design of safety campaigns, the creation of training programs, and the evaluation of road safety.